Microscopic Image Classification Using DCT for the Detection of Acute Lymphoblastic Leukemia (ALL)
Development of a computer-aided diagnosis (CAD) system for early detection of leukemia is very essential for the betterment of medical purpose. In recent years, a variety of CAD system has been proposed for the detection of leukemia. Acute leukemia is a m
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Abstract Development of a computer-aided diagnosis (CAD) system for early detection of leukemia is very essential for the betterment of medical purpose. In recent years, a variety of CAD system has been proposed for the detection of leukemia. Acute leukemia is a malignant neoplastic disorder that influences a larger fraction of world population. In modern medical science, there are sufficient newly formulated methodologies for the early detection of leukemia. Such advanced technologies include medical image processing methods for the detection of the syndrome. This paper shows that use of a highly appropriate feature extraction technique is required for the classification of a disease. In the field of image processing and machine learning approach, Discrete Cosine Transform (DCT) is a well-known technique. Nucleus features are extracted from the RGB image. The proposed method provides an opportunity to fine-tune the accuracy for the detection of the disease. Experimental results using publicly available dataset like ALL-IDB shows the superiority of the proposed method with SVM classifier comparing it with some other standard classifiers. Keywords Acute Lymphoblastic Leukemia ⋅ Discrete Cosine Transform ⋅ Watershed segmentation ⋅ CAD system
S. Mishra (✉) ⋅ L. Sharma ⋅ B. Majhi ⋅ P.K. Sa Pattern Recognition Research Lab, Department of Computer Science and Engineering, National Institute of Technology, Rourkela 769008, India e-mail: [email protected] L. Sharma e-mail: [email protected] B. Majhi e-mail: [email protected] P.K. Sa e-mail: [email protected] © Springer Science+Business Media Singapore 2017 B. Raman et al. (eds.), Proceedings of International Conference on Computer Vision and Image Processing, Advances in Intelligent Systems and Computing 459, DOI 10.1007/978-981-10-2104-6_16
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1 Introduction Acute Leukemia is a rapidly increasing disease that affects mostly the cells that are not yet fully developed. Acute Lymphoblastic Leukemia (ALL) is a significant ailment caused by the unusual growth and expansion of white blood cells [1]. ALL begins with the abnormalities starting from the bone marrow, resulting in reducing the space for red blood cells. The ALL blasts become so numerous that they flood through the red blood cells and platelets. As the cells build up, they reduce the immunity to fight with the foreign material. Hence, it is essential to treat the disease within a short span of time after making a diagnosis. As per the survey done by American Cancer Society, it has approximated that, in 2015 a total of 1,658,370 has been diagnosed, out of which 589,430 died in the US. In India, the total number of individuals suffering from leukemia was estimated to be 1,45,067 in 2014. Furthermore, as per the Indian Association of blood cancer and allied diseases, among all the cancers which is dangerous and can cause death, leukemia constitute one-third of the cases. ALL is mostly seen in children below 14 years [2]. ALL is identified with the excessive production of immature lymphoc
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